Senior Machine Learning Engineer, Public Sector
Owns the architecture, production deployment, evaluation, and improvement of agentic and generative machine learning systems for mission-critical public-sector applications. Requires 5+ years of production ML experience, strong Python and deep learning skills, architectural ownership, and an active TS clearance.
About the job
Responsibilities
- Own the end-to-end design and delivery of agent capabilities, including architecture, implementation, and evaluation.
- Define new technical patterns for unestablished problem spaces and lead their implementation.
- Put internally developed and community models into production for customer and mission-critical use cases.
- Improve production models and agents through retraining, hyperparameter tuning, and architectural updates.
- Build evaluation benchmarks, LLM judges, and verifiers to improve agent performance.
- Partner with product and research teams to scope high-impact initiatives and upcoming product lines.
- Build scalable machine learning infrastructure for ML services.
- Work with government users and subject-matter experts to inform technical direction.
- Mentor engineers, review technical work, and serve as a feasibility advisor.
- Communicate technical tradeoffs to non-technical stakeholders.
- Engineer for security and compliance constraints, including classified and resource-limited environments.
- Travel approximately 10% for customer interaction and team needs.
Requirements
- Active TS security clearance.
- 5+ years of experience building and deploying applied machine learning systems in production.
- Production experience with generative AI, agentic AI, natural language processing, deep learning, deep reinforcement learning, or computer vision.
- Experience owning architectural decisions and defending technical tradeoffs.
- Experience shipping agentic systems with production traffic and rigorous evaluation.
- Strong knowledge of algorithms, data structures, and object-oriented programming.
- Strong Python programming skills.
- Experience with PyTorch or TensorFlow.
- Experience mentoring or reviewing other engineers.
Nice-to-haves
- Graduate degree in Computer Science, Machine Learning, or Artificial Intelligence.
- Experience with AWS or Google Cloud and deploying ML models in cloud environments.
- Experience with computer vision, generative AI models, large language models, or agentic systems.
- Familiarity with ML evaluation frameworks and agentic model design.
- Experience deploying ML in classified, air-gapped, or IL5+ environments.
- Geospatial or GEOINT experience.
- Inference optimization experience.
- Fine-tuning experience with SFT, reinforcement learning, or embedding models.
Compensation
- Base salary range for Washington, DC: $235,200–$294,000 USD.
- Eligible roles may include equity and benefits such as health, dental and vision coverage, retirement benefits, learning and development stipend, PTO, and potentially a commuter stipend.
Skills
Python, PyTorch, TensorFlow, Generative AI, Agentic AI, Natural Language Processing, Deep Learning, Reinforcement Learning, Computer Vision, LLMs, AWS, GCP, Kubernetes, Machine Learning Evaluation, Geospatial Data
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